"In Parts , and , we considered newer, more specific and multi-tiered criteria by Joseph LeDoux and by Ginsburg and Jablonka for living or non-living systems to qualify as cognitive and, beyond that, as conscious agents. In Part 5, we will further explore the implications for AI. Artificial intelligence (AI) has reached remarkable heights. AI systems can diagnose diseases, play complex strategy games, pilot self-driving cars, write essays, generate code, and mimic conversation with uncanny fluency."
"In this series, we have considered two evolutionary-based frameworks to frame the debate about what counts as cognitive and what as conscious: LeDoux's model-based definition and Ginsburg and Jablonka's learning-based definition. LeDoux defined cognition as the ability to construct and use internal mental models; he distinguished three systems-non-cognitive habits/reflexes (System 1), unconscious model-based control (System 2), and conscious, deliberative cognition (System 3)."
Artificial intelligence now performs complex information-processing tasks such as diagnosis, strategic gameplay, autonomous driving, writing, coding, and conversational mimicry. Cognition can be defined broadly as acquiring, processing, and using information to guide behavior, a definition that captures many AI capabilities. Consciousness is usually defined as the capacity for subjective experience or awareness, which sets a substantially higher bar. Two evolutionary frameworks offer evaluation criteria: LeDoux's model-based account emphasizing internal model construction and three systems of control, and Ginsburg and Jablonka's learning-based account emphasizing evolutionary and developmental learning mechanisms. Debates persist about whether current AI fulfills criteria for true cognition or any form of consciousness.
Read at Psychology Today
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